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Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Social Exchange Theory02:06

Social Exchange Theory

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Social Exchange Theory01:26

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As formulated by John Thibaut and Harold Kelley, Social Exchange Theory explains human relationships as economic-like exchanges that maximize rewards and minimize costs. This theory suggests that individuals engage in relationships to gain benefits and reduce burdens, similar to economic transactions. It has been widely applied to various types of relationships, including romantic, professional, and social interactions.Rewards and Costs in RelationshipsRelationship rewards include emotional...
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Social Foundations of Self IV: Self in Digital Communication01:30

Social Foundations of Self IV: Self in Digital Communication

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Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...
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Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

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Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
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Impact of Groups on Groups01:19

Impact of Groups on Groups

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Social psychologists analyze how groups influence one another, shaping social structures and interactions through both cooperation and competition. These dynamics manifest in various ways, ranging from economic partnerships to intergroup conflicts that shape societal structures and perceptions.Cooperation and Competition in Intergroup RelationsIntergroup relationships vary across contexts, sometimes fostering cooperation and mutual benefit while at other times leading to conflict and...
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Updated: Jan 8, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
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機能的データ分析を用いたソーシャルメディアコミュニティの比較

Xiaoxia Champon1, Jasser Jasser2, Chathura Jayalath3

  • 1North Carolina State University.

Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences
|December 22, 2025
PubMed
まとめ

ソーシャルメディアコミュニティは分岐し、情報フローを形成する。投稿とリツイートの時間的データを分析することで、偽情報の戦略とコミュニティの格差が明らかになり、情報拡散の理解に不可欠である。

キーワード:
ソーシャルメディア機能的データ分析グループ差

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科学分野:

  • 社会科学
  • 計算社会科学
  • 情報科学

背景:

  • ソーシャルメディアプラットフォームは、多様な会話軌跡を持つ多様なコミュニティをホストしています。
  • 偽情報と操作されたメッセージは、世論に大きな影響を与える可能性があります。
  • グループ間の格差を理解することは、情報フローを分析するための鍵となります。

研究 の 目的:

  • 反対するソーシャルメディアコミュニティ間の格差を定量化すること。
  • これらのコミュニティがキャンペーンプロモーションに使用する明確な戦略を明らかにすること。
  • オンライングループにおける情報拡散の時間的ダイナミクスを分析すること。

主な方法:

  • 機能的データ分析を利用して、ソーシャルメディアグループの時間的ダイナミクスを調査しました。
  • 投稿やリツイートなどの時間依存メトリクスを使用してグループの行動を評価しました。
  • 著名な事件(Skripal/Novichok、Bucha Crimes)に関連するTwitterデータを調査しました。

主要な成果:

  • 予備的調査の結果、コミュニティ間の情報拡散戦略における定量的な違いが浮き彫りになった。
  • 特定のキャンペーンと相関する投稿とリツイート活動の時間的パターンが特定された。
  • 反対派のオンライングループによって採用された明確な行動メカニズムが明らかになった。

結論:

  • この研究は、ソーシャルメディアにおける情報拡散のメカニズムに関する新たな洞察を提供します。
  • コミュニティの格差を定量化することは、情報と偽情報の拡散を理解するのに役立ちます。
  • 調査結果は、オンラインキャンペーンへの最適な対応時間のための戦略に情報を提供できます。